Case Study
Building an AI Security Growth Engine: From Zero Demand to a Compounding Pipeline
Client: Amplify Security
Website: info.amplify.security
130%
Improvement in Customer Loyalty
86%
Boost in Sales
100+
Successful Branding Projects
200%
Increase in Brand Recognition
The Challenge
Amplify Security operates within an emerging and highly technical category where demand is not yet fully established.
Key constraints included:
AI code security remains nascent and not widely understood
Target buyers (CISOs, CTOs, and security engineers) require deep technical validation
Traditional lead generation models are ineffective due to extended sales cycles and trust barriers
No existing acquisition infrastructure across paid or organic channels
The mandate:
Design and deploy a scalable, compliant growth system capable of generating qualified pipeline—not just traffic.
The Strategy
VAM developed a multi-channel, full-funnel acquisition system tailored to technical decision-makers and developer behavior.
1. Intent-Based Paid Search Infrastructure
A segmented paid search architecture was deployed across:
- High-intent queries (e.g., DevSecOps, security tooling)
- Mid-funnel educational queries (guides, comparisons)
- Competitive and exploratory campaigns
Outcome: Simultaneous capture of existing demand while generating new demand within an emerging category.
2. Conversion Architecture (Signal Engineering)
Optimization was structured around high-quality engagement signals, including:
- Demo bookings
- GitHub-based signups
- Multi-step call-to-action engagement
Outcome: Platforms optimized toward qualified technical intent rather than superficial engagement metrics.
3. Multi-Path Funnel Design
Parallel conversion pathways were implemented to align with technical buyer behavior:
- “Try the Beta”
- “Book a Demo”
- “Explore the Platform”
- Developer onboarding via GitHub
Behavioral Alignment:
Learn → Validate → Test → Commit
4. Paid Media Scaling Layer
An integrated paid media strategy combined:
- Search (high-intent capture)
- Performance Max (scaling, discovery, and remarketing)
Outcome: Full coverage across demand capture, discovery, and retargeting stages.
5. SEO + AEO (Answer Engine Optimization)
A compounding organic growth system was built in parallel:
- Topic clusters centered on AI security and DevSecOps
- Structured content optimized for both search engines and LLM discovery
- Expansion into emerging, low-competition keyword spaces
Outcome: Early authority positioning within the AI code security category.
The Results
Paid Acquisition Performance
Ad Spend: $71,145
Impressions: 581,084
Cost per Conversion: $41.31
Clicks: 51,453
Average CPC: $12.41
Conversions: 5,735
Result: Established a high-volume, intent-driven acquisition engine from zero baseline.
Organic Growth (Compounded)
Over approximately 140 days (five growth cycles):
~50x increase in organic clicks
~19x increase in search impressions
Drivers of Growth:
Topic authority development
Accelerated indexing velocity
AI-aligned search strategy
Keyword Expansion
Achieved rankings for high-value, early-category queries, including:
AI code security tools
Secure code review checklist
DevSecOps automation
Developer security best practices
Result: Captured early-stage demand prior to market saturation.
Visibility Growth
+11.3% increase in search visibility during the tracked period
Rapid expansion in indexed keyword footprint
Consistent upward movement in SERP positioning
System-Level Impact
Before Engagement
No structured acquisition strategy
No defined conversion funnel
Minimal organic visibility
After Engagement
Fully integrated paid and organic growth engine
Multi-stage conversion system aligned with technical buyers
Compounding visibility and demand capture
Closed-loop data system enabling continuous optimization
Key Insight
Technical buyers do not convert on first interaction.
They require:
Education
Proof
Hands-on validation
Strategic Implication:
Success was achieved not by forcing conversion, but by engineering progressive engagement across multiple entry points.
Why This Approach Succeeded
Common Industry Failures:
Optimization for lead volume instead of qualified pipeline
Misalignment with developer and technical buyer behavior
Treating security products as traditional SaaS rather than infrastructure
VAM Approach:
Built systems rather than isolated campaigns
Optimized for downstream, high-value conversion signals
Aligned acquisition with product usage and validation behavior
Captured demand early within a developing category
Conclusion
Amplify Security now operates with:
A scalable, performance-driven paid acquisition engine
A compounding organic growth system
A conversion architecture aligned with enterprise technical buyers
Positioning:
The company is strategically positioned to lead and define demand within the AI security category as it matures.